Likelihood Formulae for generally coarsened observations from Multistate models
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| hal.structure.identifier | Epidémiologie, santé publique et développement | |
| dc.contributor.author | GÉGOUT-PETIT, Anne | |
| hal.structure.identifier | Epidémiologie, santé publique et développement | |
| dc.contributor.author | COMMENGES, Daniel | |
| dc.date.accessioned | 2024-04-04T02:46:20Z | |
| dc.date.available | 2024-04-04T02:46:20Z | |
| dc.date.created | 2005-08-30 | |
| dc.date.conference | 2005-09-29 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/191541 | |
| dc.description.abstractEn | We consider first the mixed discrete-continuous scheme of observation in multistate models; this is a classical pattern in epidemiology because very often clinical status is assessed at discrete visit times while times of death or other events are observed exactly. A heuristic likelihood can be written for such models, at least for Markov models; however, a formal proof is not easy and has not been given yet. We present a general class of possibly non-Markov multistate models which can be represented naturally as multivariate counting processes.We give a rigorous derivation of the likelihood based on applying Jacod's formula for the full likelihood and taking conditional expectation for the observed likelihood. A local description of the likelihood allows us to extend the result to a more general coarsening observation scheme proposed by Commenges & G´egout-Petit. The approach is illustrated by considering models for dementia, institutionalization and death | |
| dc.language.iso | en | |
| dc.subject.en | coarsening | |
| dc.subject.en | counting processes | |
| dc.subject.en | dementia | |
| dc.subject.en | interval-censoring | |
| dc.subject.en | likelihood | |
| dc.subject.en | Markov models | |
| dc.subject.en | multi state models | |
| dc.title.en | Likelihood Formulae for generally coarsened observations from Multistate models | |
| dc.type | Communication dans un congrès | |
| dc.subject.hal | Mathématiques [math]/Statistiques [math.ST] | |
| dc.subject.hal | Statistiques [stat]/Théorie [stat.TH] | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.conference.title | Statistical Modelling and Inference in Life Sciences | |
| bordeaux.country | DE | |
| bordeaux.conference.city | Potsdam | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-00325886 | |
| hal.version | 1 | |
| hal.invited | non | |
| hal.proceedings | non | |
| hal.popular | non | |
| hal.audience | Non spécifiée | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-00325886v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=G%C3%89GOUT-PETIT,%20Anne&COMMENGES,%20Daniel&rft.genre=unknown |
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